🧠
Mt5 Small Finetuned Billsum model by eduardorv
⭐ 26.9
🧠
Model

Mt5 Small Finetuned Billsum

by eduardorv eduardorv/mt5-small-finetuned-billsum
Free2AITools Nexus Index
26.9
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 0
P: Popularity 1
R: Recency 14
Q: Quality 65
Tech Context
0.3B Params
4.096K Ctx
Vital Performance
10 DL / 30D
Source β†’

Task categories from upstream metadata

πŸ“Content Summary

Technical Constraints

Experimental / High Latency
Low FNI signal 26.9 FNI Score
Tiny 0.3B Params
4k Context
10 Downloads
8G GPU ~2GB Est. VRAM
Dense MT5FORCONDITIONALGENERATION Architecture
Commercial APACHE License
Model Information Summary
Entity Passport
Registry ID eduardorv/mt5-small-finetuned-billsum
License Apache-2.0
Provider huggingface
πŸ’Ύ

Compute Threshold

~1.5GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{eduardorv_mt5_small_finetuned_billsum,
  author = {eduardorv},
  title = {Mt5 Small Finetuned Billsum Model},
  year = {2024},
  howpublished = {\url{https://huggingface.co/eduardorv/mt5-small-finetuned-billsum}},
  note = {Accessed via Free2AITools.}
}
APA Style
eduardorv. (2024). Mt5 Small Finetuned Billsum [Model]. Free2AITools. https://huggingface.co/eduardorv/mt5-small-finetuned-billsum

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run mt5-small-finetuned-billsum
πŸ€— HF Download
huggingface-cli download eduardorv/mt5-small-finetuned-billsum
πŸ“¦ Install Lib
pip install -U transformers

βš–οΈ Free2AITools Nexus Index V2.0

Methodology How FNI works
Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 0
Popularity (P) 1
Recency (R) 14
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Mt5 Small Finetuned Billsum: Authority (A:0), Popularity (P:1), Recency (R:14), Quality (Q:65). Semantic (S) is a query-time baseline scored live at search.

Free2AITools Nexus Index

Data Sources / Provenance

HuggingFace API GitHub Metadata Arxiv Citation DB Methodology
Open data Updated: Live data
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Deployment reference

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Technical Deep Dive

⚠️ Incomplete Data

Some information about this model is not available. Use with Caution - Verify details from the original source before relying on this data.

View Original Source β†’

πŸ“ Limitations & Considerations

  • β€’ Benchmark scores may vary based on evaluation methodology and hardware configuration.
  • β€’ VRAM requirements are estimates; actual usage depends on quantization and batch size.
  • β€’ FNI scores are relative rankings and may change as new models are added.

Social Proof

HuggingFace Hub
10Downloads
Hub Discussions
πŸ€— Data Source: Hugging Face β†—
πŸ”„ Updated daily

Source summary: Based on Hugging Face metadata. Not a recommendation.

πŸ“Š FNI Methodology πŸ“š Knowledge Baseℹ️ Verify with original source

πŸ›‘οΈ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

πŸ†” Identity & Source

id
hf-model--eduardorv--mt5-small-finetuned-billsum
slug
eduardorv--mt5-small-finetuned-billsum
source
huggingface
author
eduardorv
license
Apache-2.0
tags
transformers, tensorboard, safetensors, mt5, text2text-generation, summarization, generated_from_trainer, base_model:google/mt5-small, base_model:finetune:google/mt5-small, license:apache-2.0, endpoints_compatible, region:us

βš™οΈ Technical Specs

architecture
MT5ForConditionalGeneration
params billions
0.3
context length
4,096
pipeline tag
summarization
vram gb
1.5
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
10
stars
0
forks
0

Data indexed from public sources. Updated daily.